This notebook contains a set of analyses for analyzing EuroCultAV’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
EuroCultAV | training | published before 2020 | 41 | 0 |
EuroCultAV | validation | published 2020 | 4 | 0 |
EuroCultAV | test | published after 2020 | 4 | 0 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
EuroCultAV | Stonemaier Games | 4.9% | 0.0% | 120.48 |
EuroCultAV | Days Of Wonder | 4.9% | 0.2% | 26.05 |
EuroCultAV | Artist John Kovalic | 7.3% | 0.5% | 14.90 |
EuroCultAV | Asmodee | 31.7% | 2.6% | 12.28 |
EuroCultAV | Variable Setup | 17.1% | 1.4% | 12.05 |
EuroCultAV | Pegasus Spiele | 19.5% | 2.2% | 8.88 |
EuroCultAV | Unknown | 7.3% | 0.9% | 8.36 |
EuroCultAV | Food Cooking | 7.3% | 1.2% | 6.15 |
EuroCultAV | Take That | 24.4% | 5.1% | 4.77 |
EuroCultAV | Hasbro | 12.2% | 3.0% | 4.13 |
EuroCultAV | Hand Management | 48.8% | 20.2% | 2.42 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2019 | 286096 | Tapestry | 0.638 | no |
2 | 2016 | 169786 | Scythe | 0.257 | yes |
3 | 2017 | 226320 | My Little Scythe | 0.212 | no |
4 | 2010 | 25292 | Merchants & Marauders | 0.200 | no |
5 | 2019 | 281946 | Aftermath | 0.171 | no |
6 | 2019 | 270971 | Era: Medieval Age | 0.146 | no |
7 | 2017 | 174430 | Gloomhaven | 0.115 | no |
8 | 2013 | 146818 | Cappuccino | 0.105 | no |
9 | 2001 | 1927 | Munchkin | 0.103 | yes |
10 | 2015 | 183394 | Viticulture Essential Edition | 0.081 | no |
11 | 2017 | 197376 | Charterstone | 0.081 | no |
12 | 1959 | 7688 | Memory | 0.079 | no |
13 | 2016 | 205398 | Citadels | 0.078 | no |
14 | 2018 | 205896 | Rising Sun | 0.077 | no |
15 | 2013 | 133848 | Euphoria: Build a Better Dystopia | 0.076 | no |
16 | 2011 | 96848 | Mage Knight Board Game | 0.074 | no |
17 | 1887 | 15878 | Rummy | 0.069 | no |
18 | 2004 | 13285 | Dungeonville | 0.066 | no |
19 | 2018 | 258036 | Between Two Castles of Mad King Ludwig | 0.064 | no |
20 | 2019 | 270970 | Century: A New World | 0.057 | no |
21 | 2019 | 285984 | Last Bastion | 0.056 | no |
22 | 2019 | 230244 | Black Angel | 0.056 | no |
23 | 2013 | 128621 | Viticulture | 0.055 | no |
24 | 1800 | 45 | Perudo | 0.054 | no |
25 | 2017 | 233078 | Twilight Imperium: Fourth Edition | 0.054 | no |
26 | 2005 | 16933 | Super Munchkin | 0.052 | no |
27 | 2019 | 285774 | Marvel Champions: The Card Game | 0.049 | no |
28 | 2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.049 | no |
29 | 2014 | 152241 | Ultimate Werewolf | 0.049 | no |
30 | 2010 | 73439 | Troyes | 0.045 | no |
31 | 2018 | 257501 | KeyForge: Call of the Archons | 0.045 | no |
32 | 2013 | 127024 | Room 25 | 0.044 | no |
33 | 2016 | 171131 | Captain Sonar | 0.042 | no |
34 | 2012 | 124742 | Android: Netrunner | 0.042 | no |
35 | 2008 | 38453 | Space Alert | 0.040 | no |
36 | 2013 | 144325 | Munchkin Legends | 0.040 | no |
37 | 2018 | 209324 | The World of SMOG: Rise of Moloch | 0.037 | no |
38 | 2008 | 30549 | Pandemic | 0.037 | yes |
39 | 2010 | 62219 | Dominant Species | 0.036 | no |
40 | 2012 | 105551 | Archipelago | 0.036 | no |
41 | 2015 | 162559 | Smash Up: Munchkin | 0.036 | no |
42 | 2017 | 188920 | This War of Mine: The Board Game | 0.036 | no |
43 | 2018 | 257499 | Arkham Horror (Third Edition) | 0.035 | no |
44 | 1994 | 1552 | Illuminati: New World Order | 0.035 | no |
45 | 2019 | 272453 | KeyForge: Age of Ascension | 0.033 | no |
46 | 2012 | 123096 | Space Cadets | 0.033 | no |
47 | 2018 | 242574 | Century: Eastern Wonders | 0.032 | no |
48 | 2012 | 127023 | Kemet | 0.032 | no |
49 | 2016 | 205637 | Arkham Horror: The Card Game | 0.032 | no |
50 | 1999 | 553 | Chez Geek | 0.031 | no |
51 | 2017 | 220141 | Munchkin Shakespeare Deluxe | 0.031 | no |
52 | 2005 | 15062 | Shadows over Camelot | 0.030 | no |
53 | 1982 | 2653 | Survive: Escape from Atlantis! | 0.030 | no |
54 | 2011 | 70919 | Takenoko | 0.029 | no |
55 | 2016 | 194880 | Dream Home | 0.028 | no |
56 | 2012 | 104710 | Wiz-War (Eighth Edition) | 0.028 | no |
57 | 2016 | 208256 | Munchkin Grimm Tidings | 0.028 | no |
58 | 1977 | 2593 | Pass the Pigs | 0.028 | no |
59 | 2016 | 156858 | Black Orchestra | 0.027 | no |
60 | 2008 | 37904 | Formula D | 0.027 | no |
61 | 2017 | 162886 | Spirit Island | 0.027 | no |
62 | 1993 | 1234 | Once Upon a Time: The Storytelling Card Game | 0.026 | yes |
63 | 2005 | 18723 | Aye, Dark Overlord! The Red Box | 0.026 | no |
64 | 2017 | 195539 | The Godfather: Corleone's Empire | 0.026 | no |
65 | 2019 | 283294 | Yukon Airways | 0.026 | no |
66 | 2019 | 266192 | Wingspan | 0.026 | yes |
67 | 2006 | 25417 | BattleLore | 0.026 | no |
68 | 2007 | 30166 | The Good, the Bad, and the Munchkin | 0.025 | no |
69 | 2019 | 257700 | Munchkin Warhammer 40,000 | 0.025 | no |
70 | 2009 | 40692 | Small World | 0.025 | no |
71 | 2007 | 31481 | Galaxy Trucker | 0.025 | no |
72 | 2005 | 18258 | Mission: Red Planet | 0.025 | no |
73 | 2002 | 4604 | Chez Greek | 0.025 | no |
74 | 1995 | 13 | Catan | 0.025 | yes |
75 | 2011 | 72125 | Eclipse | 0.024 | no |
76 | 2005 | 14996 | Ticket to Ride: Europe | 0.024 | no |
77 | 2013 | 140620 | Lewis & Clark: The Expedition | 0.024 | no |
78 | 2014 | 162082 | Deus | 0.023 | no |
79 | 2004 | 12194 | Munchkin Bites! | 0.023 | no |
80 | 2017 | 234671 | Pandemic: Rising Tide | 0.023 | no |
81 | 2016 | 155821 | Inis | 0.022 | no |
82 | 2015 | 127096 | Metal Adventures | 0.022 | no |
83 | 2018 | 222509 | Lords of Hellas | 0.021 | no |
84 | 2012 | 125618 | Libertalia | 0.021 | no |
85 | 2006 | 22141 | Cleopatra and the Society of Architects | 0.021 | no |
86 | 2012 | 122522 | Smash Up | 0.021 | no |
87 | 2018 | 247236 | Duelosaur Island | 0.021 | no |
88 | 2016 | 195856 | Bloodborne: The Card Game | 0.021 | no |
89 | 2014 | 158899 | Colt Express | 0.021 | no |
90 | 2002 | 3955 | BANG! | 0.021 | no |
91 | 2004 | 9220 | Saboteur | 0.021 | no |
92 | 2014 | 163920 | Gaïa | 0.021 | no |
93 | 2004 | 9609 | War of the Ring | 0.021 | no |
94 | 2018 | 199792 | Everdell | 0.020 | no |
95 | 2010 | 65200 | Asteroyds | 0.020 | no |
96 | 2004 | 14134 | My Dwarves Fly | 0.020 | no |
97 | 2012 | 122515 | Keyflower | 0.020 | no |
98 | 2001 | 1345 | Genoa | 0.020 | no |
99 | 2011 | 79828 | A Few Acres of Snow | 0.019 | no |
100 | 2015 | 170216 | Blood Rage | 0.019 | no |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.86 |
Decision Tree | roc_auc | binary | 0.65 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think EuroCultAV is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2019 | 286096 | Tapestry | 0.638 | no |
2017 | 226320 | My Little Scythe | 0.212 | no |
2010 | 25292 | Merchants & Marauders | 0.200 | no |
2019 | 281946 | Aftermath | 0.171 | no |
2019 | 270971 | Era: Medieval Age | 0.146 | no |
What games does the model think EuroCultAV is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2006 | 25669 | Qwirkle | 0.001 | yes |
2017 | 221965 | The Fox in the Forest | 0.001 | yes |
2018 | 253664 | Taco Cat Goat Cheese Pizza | 0.001 | yes |
2018 | 244992 | The Mind | 0.001 | yes |
2008 | 40398 | Monopoly Deal Card Game | 0.001 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Android: Netrunner | Cappuccino | Ultimate Werewolf | Viticulture Essential Edition | Scythe | My Little Scythe | Rising Sun | Tapestry |
2 | Archipelago | Euphoria: Build a Better Dystopia | Deus | Smash Up: Munchkin | Citadels | Gloomhaven | Between Two Castles of Mad King Ludwig | Aftermath |
3 | Space Cadets | Viticulture | Colt Express | Metal Adventures | Captain Sonar | Charterstone | KeyForge: Call of the Archons | Era: Medieval Age |
4 | Kemet | Room 25 | Gaïa | Blood Rage | Arkham Horror: The Card Game | Twilight Imperium: Fourth Edition | The World of SMOG: Rise of Moloch | Century: A New World |
5 | Wiz-War (Eighth Edition) | Munchkin Legends | Abyss | Mysterium | Munchkin Grimm Tidings | This War of Mine: The Board Game | Arkham Horror (Third Edition) | Last Bastion |
6 | Libertalia | Lewis & Clark: The Expedition | Istanbul | Zombicide Season 3: Rue Morgue | Dream Home | Munchkin Shakespeare Deluxe | Century: Eastern Wonders | Black Angel |
7 | Smash Up | Relic Runners | Hyperborea | Between Two Cities | Black Orchestra | Spirit Island | Lords of Hellas | Marvel Champions: The Card Game |
8 | Keyflower | Rory's Story Cubes: Prehistoria | Munchkin Panic | Exploding Kittens: NSFW Deck | Inis | The Godfather: Corleone's Empire | Duelosaur Island | KeyForge: Age of Ascension |
9 | The Manhattan Project | Impulse | Sons of Anarchy: Men of Mayhem | Exploding Kittens | Bloodborne: The Card Game | Pandemic: Rising Tide | Everdell | Yukon Airways |
10 | Zombicide | Berserk: War of the Realms | Sheriff of Nottingham | 504 | Codenames: Pictures | Century: Spice Road | Gen7: A Crossroads Game | Wingspan |
11 | Zug um Zug: Deutschland | Bruxelles 1893 | Munchkin Treasure Hunt | Raptor | Codenames: Deep Undercover | Exploding Kittens: Party Pack | Pandemic: Fall of Rome | Munchkin Warhammer 40,000 |
12 | Robinson Crusoe: Adventures on the Cursed Island | Zombicide Season 2: Prison Outbreak | Akrotiri | Elysium | Aeon's End | Exploding Kittens: Newbie Edition | Fireball Island: The Curse of Vul-Kar | Paranormal Detectives |
13 | Serenissima (Second Edition) | BANG! The Dice Game | Arcadia Quest | Bastion | Star Wars: Rebellion | Pandemic Legacy: Season 2 | Azul: Stained Glass of Sintra | The Magnificent |
14 | Seasons | Zombie Kidz | Pictopia: Disney Edition | Watson & Holmes | Terraforming Mars | Sagrada | Vengeance | The King's Dilemma |
15 | Coup | Mascarade | Camel Up | Munchkin Christmas Lite | Hit Z Road | Bears vs Babies | Les Aventuriers du Rail Express | Call to Adventure |
16 | Suburbia | Glass Road | Witness | Salem 1692 | Munchkin Wonderland | Harvest Dice | Narcos: The Board Game | Zombicide: Invader |
17 | Il Vecchio | Berserk: Knights and Villains | Emperor's New Clothes | Bang! The Dice Game: The Walking Dead | Ticket to Ride: Rails & Sails | Massive Darkness | Cosmic Encounter: 42nd Anniversary Edition | Deep Blue |
18 | Descent: Journeys in the Dark (Second Edition) | Concept | Artificium | Mafia de Cuba | When I Dream | Semper Fidelis: Bitwa o Lwów 1918-1919 | Heroes of Terrinoth | The Lord of the Rings: Journeys in Middle-Earth |
19 | Love Letter | Corto | Nations: The Dice Game | T.I.M.E Stories | Ticket to Ride: First Journey (U.S.) | Azul | Star Wars: X-Wing (Second Edition) | Pandemic: Rapid Response |
20 | Munchkin Apocalypse | Rivet Wars: Eastern Front | Patchwork | Tales & Games: Little Red Riding Hood | Tales & Games: The Pied Piper | Secrets | Unlock!: Escape Adventures – In Pursuit of Cabrakan | Zombicide: Dark Side |
21 | Shadows over Camelot: The Card Game | Koryŏ | Chosŏn | Codenames | Great Western Trail | Dungeon Time | Black Mirror: NOSEDIVE | Slyville |
22 | Divinare | Tales & Games: The Three Little Pigs | Five Tribes | One Night Ultimate Werewolf: Daybreak | Smash Up: Cease and Desist | Arkham Noir: Case #1 – The Witch Cult Murders | Space Base | Machi Koro Legacy |
23 | We Will Wok You | Crossing | Black Fleet | One Night Ultimate Vampire | Pandemic: Reign of Cthulhu | Dinosaur Island | Holding On: The Troubled Life of Billy Kerr | Tainted Grail: The Fall of Avalon |
24 | Bolt Action | Pizza Party | King of New York | Pathfinder Adventure Card Game: Wrath of the Righteous – Base Set | Game of Thrones: The Iron Throne | Pirate 21 | Decrypto | Clank!: Legacy – Acquisitions Incorporated |
25 | Bee Alert | Prosperity | Onitama | Unusual Suspects | Mistfall: Heart of the Mists | Ticket to Ride: First Journey (Europe) | Treasure Island | Pharaon |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
EuroCultAV | owned | validation | GLM | roc_auc | 0.681 |
EuroCultAV | owned | validation | Decision Tree | roc_auc | 0.589 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 312804 | Pendulum | 0.081 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.050 | no |
2020 | 299592 | Beez | 0.038 | no |
2020 | 257001 | Munchkin Dungeon | 0.037 | no |
2020 | 301716 | Glasgow | 0.025 | no |
2020 | 316554 | Dune: Imperium | 0.025 | no |
2020 | 302723 | Forgotten Waters | 0.018 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.017 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.016 | no |
2020 | 298572 | Cosmic Encounter Duel | 0.016 | no |
2020 | 299939 | Doodle Dungeon | 0.016 | no |
2020 | 309630 | Small World of Warcraft | 0.015 | no |
2020 | 246900 | Eclipse: Second Dawn for the Galaxy | 0.015 | no |
2020 | 310448 | Zombie Teenz Evolution | 0.015 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.013 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.013 | no |
2020 | 301767 | Mysterium Park | 0.013 | yes |
2020 | 271524 | TIME Stories Revolution: A Midsummer Night | 0.012 | no |
2020 | 302425 | Unlock!: Mythic Adventures | 0.012 | no |
2020 | 291874 | Dwergar | 0.012 | no |
2020 | 309113 | Ticket to Ride: Amsterdam | 0.011 | no |
2020 | 308652 | Age of Dogfights: WW1 | 0.011 | no |
2020 | 282171 | Trial by Trolley | 0.010 | no |
2020 | 296912 | Fort | 0.010 | no |
2020 | 304285 | Infinity Gauntlet: A Love Letter Game | 0.010 | no |
2020 | 287742 | TIME Stories Revolution: The Hadal Project | 0.010 | no |
2020 | 312267 | Star Wars: Unlock! | 0.010 | no |
2020 | 294235 | Crime Zoom: His Last Card | 0.010 | no |
2020 | 321305 | Crime Zoom: Bird of Ill Omen | 0.010 | no |
2020 | 321306 | Crime Zoom: A Deadly Writer | 0.010 | no |
2020 | 245658 | Unicorn Fever | 0.010 | no |
2020 | 299179 | Chancellorsville 1863 | 0.010 | no |
2020 | 295905 | Cosmic Frog | 0.010 | no |
2020 | 296345 | Sherlock Holmes Consulting Detective: The Baker Street Irregulars | 0.009 | no |
2020 | 332230 | Unlock!: Heroic Adventures – Insert Coin | 0.009 | no |
2020 | 332229 | Unlock!: Heroic Adventures – Hinunter in den Kaninchenbau | 0.009 | no |
2020 | 298352 | The Shining | 0.009 | no |
2020 | 341008 | Unlock!: Heroic Adventures – Sherlock Holmes: Der scharlachrote Faden | 0.009 | no |
2020 | 327913 | Unlock!: Timeless Adventures – Arsène Lupin und der große weiße Diamant | 0.009 | no |
2020 | 300683 | Meeple Land | 0.009 | no |
2020 | 284584 | Troyes Dice | 0.009 | no |
2020 | 299169 | Spicy | 0.009 | no |
2020 | 256940 | Krosmaster: Blast | 0.009 | no |
2020 | 256317 | Guild Master | 0.008 | no |
2020 | 302417 | Mia London and the Case of the 625 Scoundrels | 0.008 | no |
2020 | 306735 | Under Falling Skies | 0.008 | no |
2020 | 289939 | Goblin Teeth | 0.007 | no |
2020 | 315196 | Dungeons & Dragons: Adventure Begins | 0.007 | no |
2020 | 304987 | Sock Monsters | 0.007 | no |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.007 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Published | ID | Name | Pr(Owned) | Owned |
2022 | 331106 | The Witcher: Old World | 0.091 | no |
2021 | 329465 | Red Rising | 0.081 | no |
2022 | 356033 | Libertalia: Winds of Galecrest | 0.067 | no |
2021 | 305682 | Rolling Realms | 0.060 | no |
2021 | 331635 | Kameloot | 0.045 | no |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.037 | no |
2021 | 285967 | Ankh: Gods of Egypt | 0.037 | no |
2021 | 298383 | Golem | 0.027 | no |
2022 | 310873 | Carnegie | 0.026 | no |
2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.018 | no |
2021 | 273330 | Bloodborne: The Board Game | 0.017 | no |
2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.017 | no |
2021 | 291859 | Riftforce | 0.015 | no |
2021 | 298069 | Cubitos | 0.015 | yes |
2021 | 314491 | Meadow | 0.015 | no |
2021 | 347137 | Chronicles of Avel | 0.015 | no |
2021 | 340466 | Unfathomable | 0.015 | no |
2021 | 290236 | Canvas | 0.015 | no |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.012 | no |
2021 | 347304 | Time's Up!: Harry Potter | 0.012 | no |
2021 | 288385 | Masters of the Night | 0.012 | no |
2021 | 332944 | Sobek: 2 Players | 0.012 | no |
2022 | 317511 | Tindaya | 0.012 | no |
2021 | 329450 | Equinox | 0.011 | no |
2021 | 339789 | Welcome to the Moon | 0.010 | no |
2021 | 344114 | Bag of Chips | 0.010 | no |
2021 | 304324 | Dive | 0.009 | no |
2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 0.009 | no |
2022 | 305096 | Endless Winter: Paleoamericans | 0.009 | no |
2021 | 328479 | Living Forest | 0.008 | no |
2021 | 343905 | Boonlake | 0.008 | no |
2021 | 291572 | Oath: Chronicles of Empire and Exile | 0.008 | no |
2021 | 277700 | Merchants Cove | 0.008 | no |
2022 | 311988 | Frostpunk: The Board Game | 0.008 | no |
2021 | 339906 | The Hunger | 0.007 | no |
2022 | 347703 | First Rat | 0.007 | no |
2021 | 295785 | Euthia: Torment of Resurrection | 0.007 | no |
2021 | 299255 | Vienna Connection | 0.007 | no |
2021 | 338834 | MicroMacro: Crime City – Full House | 0.007 | no |
2021 | 297562 | Kemet: Blood and Sand | 0.007 | no |
2021 | 344277 | Corrosion | 0.007 | no |
2022 | 338067 | 6: Siege – The Board Game | 0.007 | no |
2021 | 256680 | Return to Dark Tower | 0.007 | no |
2021 | 304336 | Million Dollar Script | 0.006 | no |
2021 | 339484 | Savannah Park | 0.006 | no |
2022 | 322524 | Bardsung | 0.006 | no |
2022 | 295770 | Frosthaven | 0.006 | no |
2022 | 351605 | Bohnanza: 25th Anniversary Edition | 0.006 | no |
2021 | 291847 | Mantis Falls | 0.006 | no |
2021 | 304985 | Dark Ages: Holy Roman Empire | 0.006 | no |
2021 | 295535 | Dark Ages: Heritage of Charlemagne | 0.006 | no |
2021 | 342942 | Ark Nova | 0.006 | no |
2022 | 308028 | Drop Drive | 0.006 | no |
2022 | 340325 | Vagrantsong | 0.006 | no |
2021 | 333144 | Stronghold: Undead (Second Edition) | 0.006 | no |
2021 | 325698 | Juicy Fruits | 0.006 | no |
2021 | 315767 | Cartographers Heroes | 0.006 | no |
2021 | 326804 | Rorschach | 0.006 | no |
2023 | 298086 | The Fog: Escape from Paradise | 0.005 | no |
2021 | 328286 | Mission ISS | 0.005 | no |
2021 | 324657 | Core Space: First Born | 0.005 | no |
2022 | 319807 | Shogun no Katana | 0.005 | no |
2022 | 299106 | Fractal: Beyond the Void | 0.005 | no |
2021 | 341169 | Great Western Trail (Second Edition) | 0.005 | no |
2022 | 342900 | Earthborne Rangers | 0.005 | no |
2021 | 290722 | Danger Park | 0.005 | no |
2022 | 332393 | Bridge City Poker | 0.005 | no |
2021 | 327721 | Ambon: Burning Sun & Little Seagulls | 0.005 | no |
2021 | 309081 | NATO: The Cold War Goes Hot – Designer Signature Edition | 0.005 | no |
2021 | 332290 | Stardew Valley: The Board Game | 0.005 | no |
2021 | 320084 | The Dogs of War | 0.005 | no |
2021 | 348461 | Castle Break | 0.005 | no |
2021 | 329713 | Dune: House Secrets | 0.005 | no |
2021 | 329714 | Dreadful Circus | 0.005 | no |
2021 | 300148 | Spy Connection | 0.005 | no |
2021 | 308948 | Talisman: Star Wars | 0.005 | no |
2022 | 349042 | A Battle Through History | 0.005 | no |
2021 | 340237 | Wonder Book | 0.005 | no |
2022 | 349793 | Age of Rome | 0.005 | no |
2021 | 337787 | Summer Camp | 0.005 | no |
2021 | 324242 | Sheepy Time | 0.005 | no |
2021 | 343847 | Dustbiters | 0.005 | no |
2021 | 306202 | Philosophia: Floating World | 0.005 | no |
2021 | 343562 | Horrified: American Monsters | 0.005 | no |
2021 | 331787 | Tiny Epic Dungeons | 0.005 | no |
2021 | 340455 | King of the Valley | 0.005 | no |
2021 | 339031 | The Goonies: Never Say Die | 0.005 | no |
2022 | 333255 | Keep the Heroes Out! | 0.005 | no |
2021 | 340677 | Bad Company | 0.005 | no |
2021 | 313730 | Harsh Shadows | 0.005 | no |
2022 | 340672 | Council of 12 | 0.005 | no |
2021 | 318184 | Imperium: Classics | 0.005 | no |
2021 | 325348 | Successors (Fourth Edition) | 0.005 | no |
2021 | 334782 | Bayou Bash | 0.005 | no |
2021 | 340041 | Kingdomino Origins | 0.005 | no |
2021 | 329084 | Space Dragons | 0.005 | no |
2021 | 299933 | Dice Flick | 0.005 | no |
2022 | 251661 | Oathsworn: Into the Deepwood | 0.004 | no |
2021 | 336195 | League of Dungeoneers | 0.004 | no |
2022 | 273814 | Deliverance | 0.004 | no |